Reflections on How a University Binge Drinking Prevention Initiative Supports Alcohol Screening, Brief Intervention, and Referral for Student Alcohol Use.
Bibliographic record
Abstract
What's Your Cap: Know When to Put a Lid on Drinking (WYC) is a student-led and research-based binge-drinking prevention campaign at the University of Saskatchewan, Canada. It was formed to encourage a culture of alcohol moderation on the university campus through peer-to-peer engagement that emphasizes promotional items and activities of interest to students. Since its development in 2011, WYC has been guided by a logic model that promotes: 1) perceived and actual student drinking norms on campus; 2) benefits of a student-led initiative; and 3) merits of working with community partners. With the release of a clinical guide in Canada for alcohol screening, brief intervention, and referral (SBIR) in 2013, WYC was prompted to consider whether it is a form of population-based SBIR. SBIR is commonly undertaken in the substance use field by health care practitioners, and this paper shares the potential for a student-based SBIR modification on a university campus.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.018 | 0.029 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".